COVID-19 vaccine uptake and effectiveness by time since vaccination in the Western Cape province, South Africa: An observational cohort study during 2020-2022

COVID-19 vaccine uptake and effectiveness by time since vaccination in the Western Cape province, South Africa: An observational cohort study during 2020-2022 | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var 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, Theuns Jacobs , Cheryl Cohen , Harry Moultrie , Richard J Lessells , Nicolette Van Der Walt , Juanita O Arendse , Hilary Goeiman , Vanessa Mudaly , Nicole Wolter , Sibongile Walaza , Waasila Jassat , Anne von Gottberg , Patrick L Hannan , Petro Rousseau , Daniel Feikin , Keith Cloete , Andrew Boulle doi: https://doi.org/10.1101/2024.01.24.24301721 Reshma Kassanjee 1 Centre for Infectious Disease Epidemiology and Research, School of Public Health, University of Cape Town , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: reshma.kassanjee{at}uct.ac.za Mary-Ann Davies 1 Centre for Infectious Disease Epidemiology and Research, School of Public Health, University of Cape Town , South Africa 2 Division of Public Health Medicine, School of Public Health, University of Cape Town , South Africa 3 Centre for Infectious Diseases Research in Africa, University of Cape Town , South Africa 4 Health Intelligence, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alexa Heekes 1 Centre for Infectious Disease Epidemiology and Research, School of Public Health, University of Cape Town , South Africa 4 Health Intelligence, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hassan Mahomed 5 Division of Health Systems and Public Health, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University , South Africa 6 Metro Health Services, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anthony J Hawkridge 7 Rural Health Services, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Milani Wolmarans 8 South African National Department of Health , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Erna Morden 4 Health Intelligence, Western Cape Government Department of Health and Wellness , South Africa 9 School of Public Health, University of Cape Town , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Theuns Jacobs 4 Health Intelligence, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cheryl Cohen 10 Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service , South Africa 11 School of Public Health, University of the Witwatersrand , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Harry Moultrie 12 Centre for Tuberculosis, National Institute for Communicable Diseases of the National Health Laboratory Service , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Richard J Lessells 13 KwaZulu-Natal Research Innovation & Sequencing Platform, University of KwaZulu-Natal , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicolette Van Der Walt 14 Emergency & Clinical Services Support, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Juanita O Arendse 5 Division of Health Systems and Public Health, Department of Global Health, Faculty of Medicine and Health Sciences, Stellenbosch University , South Africa 14 Emergency & Clinical Services Support, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hilary Goeiman 15 Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vanessa Mudaly 2 Division of Public Health Medicine, School of Public Health, University of Cape Town , South Africa 15 Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nicole Wolter 10 Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service , South Africa 16 School of Pathology, University of the Witwatersrand , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sibongile Walaza 10 Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service , South Africa 11 School of Public Health, University of the Witwatersrand , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Waasila Jassat 17 Health Practice, Genesis Analytics , South Africa 18 Division of Public Health Surveillance and Response, National Institute for Communicable Diseases of the National Health Laboratory Service , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anne von Gottberg 10 Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service , South Africa 16 School of Pathology, University of the Witwatersrand , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Patrick L Hannan 19 Division of Epidemiology and Biostatistics, School of Public Health, University of Cape Town , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Petro Rousseau 8 South African National Department of Health , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniel Feikin 20 Department of Immunizations , Vaccines, and Biologicals, World Health Organization, Switzerland Find this author on Google Scholar Find this author on PubMed Search for this author on this site Keith Cloete 15 Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew Boulle 1 Centre for Infectious Disease Epidemiology and Research, School of Public Health, University of Cape Town , South Africa 2 Division of Public Health Medicine, School of Public Health, University of Cape Town , South Africa 3 Centre for Infectious Diseases Research in Africa, University of Cape Town , South Africa 4 Health Intelligence, Western Cape Government Department of Health and Wellness , South Africa Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Background There are few data on the real-world effectiveness of COVID-19 vaccines and boosting in Africa, which experienced high levels of SARS-CoV-2 infection in a mostly vaccine-naïve population, and has limited vaccine coverage and competing health service priorities. We assessed the association between vaccination and severe COVID-19 in the Western Cape, South Africa. Methods We performed an observational cohort study of >2 million adults during 2020-2022. We described SARS-CoV-2 testing, COVID-19 outcomes, and vaccine uptake over time. We used multivariable cox models to estimate the association of BNT162b2 and Ad26.COV2.S vaccination with COVID-19-related hospitalisation and death, adjusting for demographic characteristics, underlying health conditions, socioeconomic status proxies and healthcare utilisation. Results By end 2022, only 41% of surviving adults had completed vaccination and 8% a booster dose, despite several waves of severe COVID-19. Recent vaccination was associated with notable reductions in severe COVID-19 during distinct analysis periods dominated by Delta, Omicron BA.1/2 and BA.4/5 (sub)lineages: within 6 months of completing vaccination or boosting, vaccine effectiveness was 46-92% for death (range across periods), 45-92% for admission with severe disease or death, and 25-90% for any admission or death. During the Omicron BA.4/5 wave, within 3 months of vaccination or boosting, BNT162b2 and Ad26.COV2.S were each 84% effective against death (95% CIs: 57-94 and 49-95, respectively). However, there were distinct reductions of VE at larger times post completing or boosting vaccination. Conclusions Continued emphasis on regular COVID-19 vaccination including boosting is important for those at high risk of severe COVID-19 even in settings with widespread infection-induced immunity. Introduction Globally we have transitioned from emergency to long-term management of COVID-19 with reduced COVID-19 severity and high levels of population immunity from both prior infection and vaccination. 1 A key component of long-term management is optimizing vaccination strategies to protect those at high risk of severe COVID-19 as protection conferred by infection or vaccination against severe disease may wane 2 – 4 and there remains uncertainty about future SARS-CoV-2 evolution. However, the value of continued provision of vaccination opportunities is unclear in Africa and low-and middle-income countries (LMICs) where there were high levels of infection before vaccination became available; 5 , 6 achieving primary vaccine and especially booster uptake has been challenging; 7 and there are competing health service priorities such as HIV and tuberculosis, many of which were adversely affected during the COVID-19 pandemic. 8 – 11 While most of those vaccinated in LMICs are likely to have hybrid immunity (prior infection and vaccination) 5 , 6 which has been shown to provide the most durable protection against severe disease in high-income country studies, there are few studies of long-term vaccine effectiveness in the context of very high levels of infection before vaccine availability, as experienced in countries such as South Africa (SA). 2 While a health insurance scheme in SA showed rapid waning of protection of BNT162b2 vaccination against severe disease, with restoration by booster vaccination, applicability to the uninsured, poorer population is unclear. 12 Uninsured persons likely have higher levels of prior infection than the insured and a different comorbidity burden, and are more similar to populations from other LMICs. Real-world data on durability of vaccine protection in these populations are needed to assess the benefit of ongoing COVID-19 vaccination in these contexts. By merging multiple data sources curated by the Western Cape Government Department of Health and Wellness (WCGHW), we studied the association of COVID-19 vaccination with three COVID-19 hospitalisation and death outcomes amongst >2 million adult public sector healthcare users in the Western Cape (WC) province of SA. We studied this association over time (from vaccine rollout through three subsequent COVID-19 waves through end 2022); and differentiated vaccine state by type of vaccine (Ad26.COV2.S or BNT162b2), completeness of primary vaccination, and time in the vaccine state. The WCGHW regularly shared latest results from this study with advisory groups to inform the provincial and national vaccination program. Methods Study population, study period, and data sources We studied adult (aged ≥18 years) public sector healthcare users (≥1 public sector healthcare encounter in the five years preceding 1 March 2020, the start of the COVID-19 pandemic) in the WC, who had a civil identification number enabling linkage to the national death registry. We excluded persons vaccinated before 17 May 2021, as earlier vaccination was restricted to healthcare workers. The Western Cape Provincial Health Data Centre (PHDC) compiles de-identified person-level longitudinal data by integrating patient data from multiple information systems (administrative, laboratory, pharmacy, hospital and disease management) in all public sector health facilities in the province. 13 These data are used to infer various health conditions, with estimated onset dates. Additionally, for this analysis, the dates and types of administered COVID-19 vaccines were obtained from the national Electronic Vaccine Data System (EVDS). 14 Data on all positive and negative SARS- CoV-2 PCR and antigen tests were obtained from public or private laboratories, or from consolidated laboratory data assembled by the National Institute for Communicable Diseases (NICD). 15 PHDC public sector hospital data were supplemented by data on private sector COVID-19 admissions from the NICD hospital surveillance system (DATCOV). 16 , 17 Data were linked to the national vital registration system to complete ascertainment of mortality. 18 , 19 Data were extracted during February 2023 after which SA has not experienced substantial surges in documented SARS-CoV-2 infections. The cohort was studied from 1 Jan 2020 until 31 Dec 2022, to allow for delays in outcome ascertainment. During this period, SA experienced five distinct COVID-19 waves with a different SARS-CoV-2 (sub)lineage dominating in each. For this study, each ‘wave’ period began when the dominant virus (sub)lineage first accounted for ≥20% of the week’s sequenced specimens nationally, and continued until the next wave. The five wave periods, derived in Appendix A1 , correspond to the Ancestral (starting 1 Mar 2020), Beta (18 Oct 2020), Delta (30 May 2021), Omicron BA.1 or BA.2 (14 Nov 2021), and Omicron BA.4 or BA.5 (3 Apr 2022-2 Jul 2022) (sub)lineages. The study was approved by the University of Cape Town Health Research Ethics Committee (HREC REF 460/2020) and WCGHW. Individual informed consent requirement was waived for this analysis of de-identified data. Definition of outcomes We aimed to study severe COVID-19 and defined three COVID-19 outcomes, with each successive outcome (as ordered below) using a stricter definition of ‘severe’ disease, noting that some patients who died from COVID-19 were not hospitalised. Our outcomes were SARS-CoV-2 diagnoses associated with COVID-19 related (1) hospital admission (with disease of any severity), or death; (2) hospital admission with severe disease (i.e., requiring an intensive care unit or steroid prescription), or death; and (3) death alone. An admission or death was deemed COVID-19 related if sufficiently close to the SARS-CoV-2 diagnosis date, with no record of non-natural causes – see definitions in Appendix A2 . SARS-CoV-2 testing was extremely limited in SA: seroprevalence studies suggest approximately 1 in 10 infections were diagnosed, 6 and there was negligible use of self-tests during the study period. Therefore, ‘any SARS-CoV-2 diagnosis’ was not studied as an outcome. Definition of vaccine states Vaccines became available to the general population on 17 May 2021, with the minimum eligibility age progressively reducing from 60 years to 12 years by 20 October 2021. As the primary vaccination series, persons either received the single-dose Janssen Ad26.COV2.S or two-dose Pfizer-BioNTech BNT162b2 vaccine, though immunocompromised individuals were eligible for an additional homologous vaccine dose. From January 2022, all adults could receive additional booster doses 180 days after last doses. In the analyses, persons could move through different vaccine states over time, from being ‘unvaccinated’, briefly into a ‘transition’ state (<28 days after Ad26.COV2S or <21 days after BNT162b2) immediately after receiving their first dose of any vaccine, and then among three vaccinated states. At any time, a vaccinated person could have received a ‘Complete Ad26.COV2S’ (≥28 days after single dose), ‘Incomplete BNT162b2’ (no second dose, or <14 days thereafter) or ‘Complete BNT162b2’ (≥14 days after second dose) vaccination series. Among those with complete vaccination, we did not explicitly disaggregate by number of boosters due to limited booster uptake, and instead distinguished by ‘time in state’ (<3, 3-5, 6-8 and ≥9 months): this time started increasing from zero upon entering the vaccine state, and restarted (from zero) seven days after any booster dose. See Appendix A3 for detailed definitions. We considered only the type of the first vaccine, as very few persons received heterologous doses. Statistical methods We described over time the rate of each COVID-19 outcome, as well as the proportions of: those people with a documented SARS-CoV-2 infection who experienced each COVID-19 outcome, SARS-CoV-2 tests that were positive, and people in each vaccine state. To estimate the association of vaccination with each outcome, we used a cox proportional hazards model with time-varying vaccine terms (vaccine state and time in state) and covariates, and parameterized it to allow the outcome rate to vary with calendar time. In SA, by definition, persons could not acquire a new SARS-CoV-2 infection within 90 days of the start of a previous documented infection, and were therefore removed from the at-risk population during these periods. People were censored at deaths that were not COVID-19 related. ‘Vaccine effectiveness’ (VE) was defined as one minus the model-estimated hazard ratio describing the rate of the outcome in a chosen vaccinated state versus in the reference unvaccinated state. We adjusted for several covariates, and continuous covariates were categorised a priori. Demographic characteristics were sex and (time-varying) age. Time-varying health conditions were diabetes, hypertension, chronic kidney disease, chronic respiratory disease, HIV, ‘any’ tuberculosis (previous or ongoing), an ‘ongoing’ tuberculosis episode, pregnancy and a prior SARS-CoV-2 diagnosis. Location (subdistrict/district) and location type for the most recent primary healthcare facility visit (within Cape Town Metro, versus non-Metro or no recorded visit) were potential measures of socioeconomic status and healthcare access. The number (total for 5 years) and regularity (number of years with visits in 3 years) of primary healthcare facility visits before the pandemic (March 2020), and the number of negative SARS-CoV-2 tests more than 90 days before each analysis period (defined below), acted as proxies for other health risks and service use. All covariates were entered as main effects, though we used a likelihood ratio test (LRT) to investigate modification of VE by HIV status. Appendix A4 contains detailed definitions of covariates. Given the complexity of the evolving virus, setting and study population, we expected associations of COVID-19 outcomes with vaccination and covariates to change over our study period. We therefore fitted separate models to each of the analysis wave periods (defined above) from vaccine rollout, interpreting each estimated VE as an average VE over that period. As supplementary analyses, we examined VE for distinct subpopulations based on sex, age and HIV status at start 2020, and when excluding people who received heterologous doses. We also estimated VE over short 6-week rolling windows of time. Results Description of cohort characteristics, vaccination and COVID-19 outcomes Among 2,429,927 WC adult public sector healthcare users at start 2020, median age was 38 years (inter-quartile range: 28,52), and 60% were female ( Table 1 ). There was a high burden of inferred non-communicable conditions (end 2022: 23% and 10% had hypertension and diabetes, respectively; 8% and 4% had chronic respiratory disease and chronic kidney disease) and inferred infectious conditions (15% and 10% were living with HIV and had ever experienced tuberculosis). View this table: View inline View popup Download powerpoint Table 1: Demographic characteristics and non-communicable and infectious conditions in the cohort of South African adults utilising public sector healthcare in the Western Cape province, studied during calendar years 2020 through 2022, also stratified by completion of a primary COVID-19 vaccination series by end 2022. Percent (count frequency) is reported. Only 40% of the cohort studied from 2020 was completely vaccinated by end 2022 ( Table 2 ), and 8% received a booster. Heterologous doses were received by only 28 persons during primary vaccination, and by <1.5% of vaccinated persons during boosting. About 1 in 200 experienced COVID-19 related death; 1 in 150 COVID-19 related hospitalisation with severe disease, or death; and 1 in 60 COVID-19 related hospitalisation, or death. 21% of COVID-19 related deaths occurred without a COVID-19 related hospitalisation. View this table: View inline View popup Download powerpoint Table 2: COVID-19 vaccination, SARS-CoV-2 testing, and COVID-19 outcomes all as at end 2022, in the cohort of South African adults utilising public sector healthcare in the Western Cape province, studied during calendar years 2020 through 2022, also stratified by completion of a primary COVID-19 vaccination series by end 2022. Percent (count frequency) is reported. During the five COVID-19 waves of 2020-2022, weekly SARS-CoV-2 diagnoses reached a highest peak of 17 per 100 person years and test positivity reached 54%; with high overall mortality (6%) in those with documented SARS-COV-2 infection ( Figure 1A - 1C ). Vaccines were available from mid-2021. By start 2022, 38% of the surviving cohort were completely vaccinated, with limited further vaccine uptake ( Figure 1D ). By end 2022, 5% of the surviving cohort had an incomplete vaccination series; and 41% had a complete series (71% BNT162b2), of whom only 3% completed or boosted vaccination within the last 6 months. Download figure Open in new tab Figure 1: COVID-19 outcomes, SARS-CoV-2 testing and positivity, and COVID-19 vaccination in the cohort of South African adults utilising public sector healthcare in the Western Cape province, over time, through the COVID-19 pandemic period. (A) Rates of SARS-CoV-2 diagnoses and COVID-19-associated hospitalisation and death outcomes, per week (B) Proportions of persons with SARS-CoV-2 diagnoses who experienced COVID-19 outcomes, per 4-week period, with overall proportions over the full plotted period indicated. (C) SARS-CoV-2 test positivity proportions, per week. (D) Proportions of the population in different vaccine states, at the end of each calendar month. Dashed vertical lines separate wave periods. Grey vertical bands indicate each wave’s peak SARS-CoV-2 diagnoses weeks. Comparing vaccination over time by age group ( Figure 2 ), vaccine uptake was highest in the oldest persons (end 2022: 33% and 51% completely vaccinated among 18-34 and ≥60-year-old persons, respectively). During the Omicron periods (end 2021 through 2022), completion of vaccination series and booster uptake was also highest in oldest persons (end 2022: 4% and 19% with boosters in 18-34 and ≥60-year-olds, respectively). Download figure Open in new tab Figure 2: Primary series vaccination and booster uptake in the cohort of South African adults utilising public sector healthcare in the Western Cape province: Proportions of the surviving population in the different vaccinated states a , at the end of each calendar month (x-axis), by age group in years (based on age at start 2020) (figure columns). See Appendix B1 for tables of all analysis variables, including by age group; and Appendix B2 for plots of outcomes, testing and vaccination over time, by sex, age group and HIV status. Vaccine effectiveness estimates Before adjusting for time in vaccinated state, there was substantial variation in estimated VE by COVID-19 outcome and wave period ( Figure 3 ): outcome rates ranged from 20 to 92% lower in completely vaccinated (versus unvaccinated). When accounting for time in vaccine state, VE was high among those who most recently completed or boosted vaccination (i.e., within three months), for all wave periods and outcomes – point estimates were in the range of 54-92% for death, 51-92% for admission with severe disease or death, and 38-90% for any admission or death. However, there was a distinct reduction of VE with longer durations after completing or boosting vaccination – on average, VE point estimates reduced by about 25% then 50% when moving from <3 months to 3-5 months and then to 6-8 month post-vaccination in turn, though uncertainties often became large at 6-8 months. Download figure Open in new tab Figure 3: Vaccine effectiveness estimates (x-axis), for different vaccinated states a and wave periods (figure rows) and COVID-19 outcomes (figure columns), by time b in the vaccinated state (y-axis). Vaccine effectiveness represents the reduction in outcome rates for vaccinated persons versus unvaccinated persons, adjusting for all covariates. Markers indicate point estimates, horizontal error bars represent 95% confidence intervals. Considering the type of vaccine, within 3 months of completing or boosting vaccination in the Delta wave, at a point estimate level, the VE of BNT162b2 (90-92% across outcomes) was higher than for Ad26.COV2.S (62-67%), while the two vaccines’ VE were often more similar over the Omicron periods for similar times in vaccine state. During the most recent Omicron BA.4/5 period and for the most severe outcome of death, within 3 months, BNT162b2 and Ad26.COV2.S were each 84% effective against death (95% CIs: 57-94 and 49-95, respectively). We were unable to detect differences in VE by HIV status (p-values for LRTs by outcome and wave periods mostly ≫ 0.05). Appendix B3 reports VE estimates for subpopulations, which all had reduced rates of outcomes when recently vaccinated, though uncertainties can be large. Appendix B4 presents estimated hazard ratios for all covariates in the multivariable cox models. Appendix B5 demonstrates the steady decline in VE measured over 6-week rolling windows of time that could be explained by factors such as increasing times in vaccine state (not accounted for in this analysis), testing practices, and growing mismatch between vaccine and dominant infection (sub)lineage. Appendix A5 presents a theoretical exploration of the magnitude of bias in estimating VE resulting from the under-ascertainment of prior infection. Discussion To our knowledge, this is the largest observational cohort study of COVID-19 VE in an African population with high levels of infection before vaccines became available and low overall vaccination uptake; and ongoing updates of this study’s results were used in real-time to inform SA’s vaccination programme. By end 2022, only 41% of adults had received primary vaccination and 8% a booster. VE against severe COVID-19 involving hospitalisation or death was high within 3 months of completing or boosting vaccination, including during periods when more recent Omicron (sub)lineages dominated: BNT162b2 and Ad26.COV2S were >80% effective against death during the Omicron BA.4/5 period, and VE point estimates varied within 38-92% across distinct wave periods and outcomes. However, we found distinct reductions of VE at larger times post completing or boosting vaccination during the Omicron periods. Our assessment of VE durability against severe COVID-19 following recent primary or booster vaccination in a setting of high levels of SARS-CoV-2 infection before vaccination provides an important extension of results from others settings: a systematic review including five studies of hybrid protection conferred by both confirmed prior infection and vaccination against severe COVID-19 (hospitalisations or severe disease) showed durable protective VE >90% (compared to persons unvaccinated without prior infection) for up to 12 months following primary vaccination and 6 months following boosting, before and during the Omicron period. 2 , 20 – 24 However, the review did not include any studies from Africa or settings with high levels of SARS-CoV-2 infection before Omicron emergence, 5 , 25 follow-up after booster vaccination was limited and results were variable. 21 , 23 Our results from a cohort study are not directly comparable with these mostly test-negative case-control studies which examined the association of COVID-19 outcomes with confirmed hybrid protection (vaccination and prior infection) specifically in samples of only people with respiratory symptoms and testing for SARS-CoV-2 infection. Our study considered a general population, and, given the substantial under-ascertainment of SARS-CoV-2 infections in our setting, we could not robustly assess hybrid immunity. However, our results of high VE that reduced at longer durations post-vaccination were similar to three studies of severe COVID-19 during the Omicron period included in the review: In a Swedish study, VE from hybrid immunity was >80% after ≥3 vaccine doses but 54% (95% CI: 13,75) with only 2 doses. 24 In a Czech study, VE conferred by hybrid immunity declined at >2 months since last vaccine (primary series or booster). 21 In a USA study, among people with prior infection and ≥5 months after primary vaccination, the VE of boosting was 56% (95% CI: 44,66). 26 Strengths of our study include using routinely collected longitudinal observational data to assess real-world VE with a cohort design in a large population of relevance to many LMICs. We had robust ascertainment of vaccination through linkage to EVDS; and of SARS-CoV-2 testing, admissions, and deaths, through linkage to NICD records and vital registration. We also adjusted for known health conditions, health service utilisation and testing behaviour. Using routinely collected observational data also confers several limitations. First, there may be unmeasured confounding. For example, from a healthy vaccinee bias (inflating VE measures) 27 or greater health-seeking behaviour for COVID-19 disease among the vaccinated (deflating VE measures). Our adjustment for prior SARS-CoV-2 infections was also extremely limited – there was substantial under-ascertainment of infections in the WC throughout the pandemic, which likely increased with the emergence of the Omicron lineage. 6 Second, low booster uptake limited our ability to assess the effectiveness of boosters themselves or distinguish between homologous/heterologous boosting. 14 Third, there may be misclassification of outcomes. Identifying the outcome required a positive SARS-CoV-2 test in those admitted or deceased, which would be impacted by testing practices and the use of antigen (versus PCR) tests which varied over time. We have previously shown the decrease in the specificity of identifying COVID-19 related hospitalisations and deaths with the emergence of Omicron BA.1/2 and widespread testing of all admitted patients. 28 29 This may contribute to a deflation in VE estimates in this study during the Omicron BA.1/2 wave, compared to in the BA.4/5 wave when only those with clinically suspected COVID-19 were tested. Also, data on recorded steroid prescription to identify ‘admissions with severe disease’ were only available for public sector admissions. Lastly, we were only able to assess changes in VE with time post-vaccination during the later Omicron periods. Conclusions Even in our population with high levels of immunity from prior infection, recently completing or boosting COVID-19 vaccination (<6 months previously) provided protection against severe COVID-19, but this protection reduced at longer durations since last vaccine dose. Continued opportunities for COVID-19 primary vaccination and boosting of vulnerable populations should be provided irrespective of levels of prior SARS-CoV-2 infection. Data Availability The data are not publicly available due to privacy or ethical restrictions. The data that support the findings of this study can be requested from the Western Cape Provincial Health Data Centre (WCPHDC) [ https://www.westerncape.gov.za/general-publication/provincial-health-data-centre ]; restrictions apply to the availability of these data. Conflicts of interest MD reports grants from Viiv Healthcare, outside the submitted work. CC reports grants from Sanofi Pasteur, US Centers for Disease Control and Prevention (CDC), Wellcome Trust, South African Medical Research Council (SAMRC) and the Bill & Melinda Gates Foundation. NW reports grants from the Bill and Melinda Gates Foundation and Sanofi. SW reports grants from US CDC and Bill and Melinda Gates Foundation. AvG reports grants from the World Health Organisation Regional Office for Africa (WHO-AFRO), US CDC, SAMRC, Fleming Fund, Africa Centres for Disease Control / African Society for Laboratory Medicine. AB reports grants from the US National Institutes for Health, Bill and Melinda Gates Foundation and the Wellcome Trust. Funding This work was supported by funding from the Western Cape Government Department of Health and Wellness for the Western Cape Provincial Health Data Centre, the US National Institutes for Health [R01 HD080465, U01 AI069924], the Bill and Melinda Gates Foundation [1164272, 1191327], the United States Agency for International Development [72067418CA00023], the European Union [101045989], the Grand Challenges ICODA pilot initiative delivered by Health Data Research UK and funded by the Bill & Melinda Gates and Minderoo Foundations [INV-017293], and the Wellcome Trust [203135/Z/16/Z, 222574]. The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of this report. The opinions, findings and conclusions expressed in this manuscript reflect those of the authors alone. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Acknowledgments AB, RK and MD conceived the study. AH prepared the data extracts. RK designed and implemented the analysis, with inputs from MD, AB and LH. RK drafted and revised the manuscript, with contributions by MD. All authors reviewed the manuscript, provided inputs and approved the manuscript. We would like to acknowledge all patients in the Western Cape and to thank the Western Cape Department of Health Provincial Health Data Centre (WCPHDC), the South African National Department of Health and the Electronic Vaccine Data System (EVDS), the National Institute for Communicable Diseases (NICD), the Network for Genomic Surveillance in South Africa (NGS-SA), the South African COVID-19 Variant Consortium, the South African Medical Research Council (SAMRC) and the Western Cape Government Department of Health and Wellness (WCGHW) Communicable Disease Control sub-directorate as well as all those involved in the Western Cape COVID-19 response and vaccination programme for their contributions to this report. Data is not publicly available. References 1. ↵ Wise J . COVID-19: WHO declares end of global health emergency . BMJ 2023 ; 381 : p1041 . 2. ↵ Bobrovitz N , Ware H , Ma X , et al. 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Changes to the way we report on COVID-19 deaths [Accessed 8 January 2024 , at https://ukhsa.blog.gov.uk/2023/01/27/changes-to-the-way-we-report-on-covid-19-deaths ]. View the discussion thread. Back to top Previous Next Posted January 25, 2024. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following COVID-19 vaccine uptake and effectiveness by time since vaccination in the Western Cape province, South Africa: An observational cohort study during 2020-2022 Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. 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Share COVID-19 vaccine uptake and effectiveness by time since vaccination in the Western Cape province, South Africa: An observational cohort study during 2020-2022 Reshma Kassanjee , Mary-Ann Davies , Alexa Heekes , Hassan Mahomed , Anthony J Hawkridge , Milani Wolmarans , Erna Morden , Theuns Jacobs , Cheryl Cohen , Harry Moultrie , Richard J Lessells , Nicolette Van Der Walt , Juanita O Arendse , Hilary Goeiman , Vanessa Mudaly , Nicole Wolter , Sibongile Walaza , Waasila Jassat , Anne von Gottberg , Patrick L Hannan , Petro Rousseau , Daniel Feikin , Keith Cloete , Andrew Boulle medRxiv 2024.01.24.24301721; doi: https://doi.org/10.1101/2024.01.24.24301721 Share This Article: Copy Citation Tools COVID-19 vaccine uptake and effectiveness by time since vaccination in the Western Cape province, South Africa: An observational cohort study during 2020-2022 Reshma Kassanjee , Mary-Ann Davies , Alexa Heekes , Hassan Mahomed , Anthony J Hawkridge , Milani Wolmarans , Erna Morden , Theuns Jacobs , Cheryl Cohen , Harry Moultrie , Richard J Lessells , Nicolette Van Der Walt , Juanita O Arendse , Hilary Goeiman , Vanessa Mudaly , Nicole Wolter , Sibongile Walaza , Waasila Jassat , Anne von Gottberg , Patrick L Hannan , Petro Rousseau , Daniel Feikin , Keith Cloete , Andrew Boulle medRxiv 2024.01.24.24301721; doi: https://doi.org/10.1101/2024.01.24.24301721 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Epidemiology Subject Areas All Articles Addiction Medicine (574) Allergy and Immunology (865) Anesthesia (304) Cardiovascular Medicine (4460) Dentistry and Oral Medicine (445) Dermatology (383) Emergency Medicine (611) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1517) Epidemiology (15250) Forensic Medicine (31) Gastroenterology (1132) Genetic and Genomic Medicine (6621) Geriatric Medicine (669) Health Economics (1002) Health Informatics (4563) Health Policy (1372) Health Systems and Quality Improvement (1617) Hematology (544) HIV/AIDS (1272) Infectious Diseases (except HIV/AIDS) (15936) Intensive Care and Critical Care Medicine (1107) Medical Education (624) Medical Ethics (147) Nephrology (670) Neurology (6640) Nursing (346) Nutrition (1001) Obstetrics and Gynecology (1148) Occupational and Environmental Health (957) Oncology (3350) Ophthalmology (981) Orthopedics (369) Otolaryngology (421) Pain Medicine (436) Palliative Medicine (130) Pathology (665) Pediatrics (1698) Pharmacology and Therapeutics (693) Primary Care Research (714) Psychiatry and Clinical Psychology (5464) Public and Global Health (9258) Radiology and Imaging (2211) Rehabilitation Medicine and Physical Therapy (1372) Respiratory Medicine (1198) Rheumatology (598) Sexual and Reproductive Health (716) Sports Medicine (533) Surgery (715) Toxicology (100) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a03873ec4ab10db4',t:'MTc4MDA4ODY4MA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();